Abstract

Environmental concerns comprising pollution and global warming are among the key
parameters that steer policy making actions regarding sustainability. Energy industry that
comprises energy generation, distribution, and transmission phases of energy loop is at the
core of these concerns and faces challenges. Due to handling capabilities, present electricity
grid is not robust enough to utilize desired level of renewable energy sources due to their
intermittent nature. On the other hand, emerging policies are targeting the increased
utilization of renewable energy sources. In the light of environmental policies and increased
stability requirements of the electricity grids, a new concept called “smart grid” emerges.
Smart grids are intended to eliminate the limitations of present electricity grids such as
offering increased handling capacity for renewable energy, increased interaction of the
consumers with the utilities, and increased supply and demand management. It is not easy to
express a solid smart grid definition as each party (energy generation, distribution, and
demand side management) has its own approach in line with the desires. Due to the potential
environmental benefits of smart grids, some governments engage smart grid projects to their
agenda. As solid smart grid definition does not exist, there is no available solid strategy for
smart grid implementations. On the other hand, it is well understood that failure in
deployment of smart grids (regardless of the technology) will have undesirable impacts on
growth of renewable energy generation, and failure in meeting EU carbon targets
consequently. This research seeks to develop a model that seeks optimization of smart grid
implementations, and it assists decision makers with deciding on the priory areas for smart
grid applicability. Stated areas in this case are neighbourhoods comprising of residential
buildings where considerable amount of energy is consumed. A set of criteria regarding to
residential energy use and renewable energy technologies, are defined in the study. Proposed
model is embedded in a GIS platform, and the main process carried out is a prioritization
mechanism that comprises Analytical Hierarchy Process (AHP) and geospatial computations
like clustering and regression analysis in order to evaluate the alternative neighbourhoods.
Proposed model optimizes smart grid projects by ranking of alternatives in terms of smart
grid applicability. Such an aid in optimizing smart grid projects has the potential to maintain
progress of smart grids in a timely manner.